iTASC: a Tool for Multi-Sensor Integration in Robot Manipulation

被引:0
|
作者
Smits, Ruben [1 ]
De Laet, Tinne [1 ]
Claes, Kasper [1 ]
Bruyninckx, Herman [1 ]
De Schutter, Joris [1 ]
机构
[1] Katholieke Univ Leuven, Dept Mech Engn, B-3001 Louvain, Belgium
来源
2008 IEEE INTERNATIONAL CONFERENCE ON MULTISENSOR FUSION AND INTEGRATION FOR INTELLIGENT SYSTEMS, VOLS 1 AND 2 | 2008年
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
iTASC (acronym for 'instantaneous task specification and control') ill is a systematic constraint-based approach to specify complex tasks of general sensor-based robot systems. iTASC integrates both instantaneous task specification and estimation of geometric uncertainty in a unified framework. Automatic derivation of controller and estimator equations follows from a geometric task model that is obtained using a systematic task modeling procedure. The approach applies to a large variety of robot systems (mobile robots, multiple robot systems, dynamic human-robot interaction, etc.), various sensor systems, and different robot tasks. Using an example task, this paper shows that iTASC is a powerful tool for multi-sensor integration in robot manipulation. The example task includes multiple sensors: encoders, a force sensor, cameras, a laser distance sensor and a laser scanner. The paper details the systematic modeling procedure for the example task and elaborates on the task specific choice of two types of task coordinates: feature coordinates, defined with respect to object and feature frames, which facilitate the task specification, and uncertainty coordinates to model geometric uncertainty. Experimental results for the example task are presented.
引用
收藏
页码:162 / 169
页数:8
相关论文
共 50 条
  • [41] A method of cliff detection in robot navigation based on multi-sensor
    Su, Zhilong
    Wang, Can
    Li, Yuxiao
    Wu, Xinyu
    2020 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE-RCAR 2020), 2020, : 152 - 157
  • [42] Research of multi-sensor ranging system based on soccer robot
    Liu, Zai-Xin
    Zhang, Jin-Yong
    Wang, Jin-Ge
    Luo, Xu-Dong
    Deng, Xing-Qiao
    Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 2010, 42 (SUPPL. 2): : 253 - 256
  • [43] Mobile robot localization by multi-sensor fusion and scene matching
    Yang, YB
    Tsui, HT
    INTELLIGENT ROBOTS AND COMPUTER VISION XV: ALGORITHMS, TECHNIQUES, ACTIVE VISION, AND MATERIALS HANDLING, 1996, 2904 : 298 - 309
  • [44] Software design based on COM for multi-sensor robot system
    Wang, J.
    Su, J.
    Xi, Y.
    2001, Nanjing University of Aeronautics an Astronautics (16):
  • [45] Multi-Sensor Orientation Tracking for a Facade-Cleaning Robot
    Vega-Heredia, Manuel
    Muhammad, Ilyas
    Ghanta, Sriharsha
    Ayyalusami, Vengadesh
    Aisyah, Siti
    Elara, Mohan Rajesh
    SENSORS, 2020, 20 (05)
  • [46] Multi-sensor Fusion Glass Detection for Robot Navigation and Mapping
    Wei, Hao
    Li, Xue-en
    Shi, Ying
    You, Bo
    Xu, Yi
    2018 WRC SYMPOSIUM ON ADVANCED ROBOTICS AND AUTOMATION (WRC SARA), 2018, : 184 - 188
  • [47] A multi-sensor fusion method based on EKF on granary robot
    Zhang, Wenhou
    Liu, Jin
    Wang, Jiao
    PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020), 2020, : 4838 - 4842
  • [48] Transportation robot based on multi-sensor fusion and machine vision
    Pang, Renning
    Cao, Jianzhao
    Wang, Yuxia
    Qi, Yuanwei
    Sun, Liangliang
    2022 34TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2022, : 6282 - 6287
  • [49] Implementation of multi-sensor information fusion in the mobile robot control
    Qiu, Guoqing
    Yu, Yongcan
    Li, Ming
    Long, Yi
    RENEWABLE ENERGY AND ENVIRONMENTAL TECHNOLOGY, PTS 1-6, 2014, 448-453 : 3549 - 3552
  • [50] Multi-sensor Fusion Based Indoor Mobile Robot Localization
    Liu, Rui
    Xu, Jun
    Lou, Yunjiang
    Chen, Haoyao
    2022 IEEE 18TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2022, : 22 - 27